A number of techniques have been proposed to enable extraction of the foreground from an image, for example, the extraction of a person from a digital image showing the person standing in front of a scenic view. This process of splitting an image into the foreground and background is known as image segmentation. Image segmentation comprises labeling image elements (such as pixels, groups of pixels, voxels or groups of voxels) as either a foreground or a background image element. This is useful in digital photography, medical image analysis, and other application domains where it is helpful to find a boundary between an object in the image and a background. The extracted object and the background may then be processed separately, differently, etc. For example, in the case of a medical image it may be appropriate to segment out a region of an image depicting a tumor or organ such as the lungs in order to enable a surgeon to interpret the image data.
Dependent upon the technique used, the amount of user input that is involved to achieve the segmentation can vary significantly and in some systems a user traces the approximate outline of the object to be extracted. In other systems, the user draws a box on the image which contains the object of interest. This box is used to specify foreground and background training data which can then be used in segmenting the image.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known image segmentation techniques.